Amazon Bedrock Model Provider

To use an embedding model deployed to AWS Bedrock service, specify the model endpoint name prefixed with bedrock: in the from field and include the required parameters in the params section.

Parameters

AWS Parameters

Parameter	Description
aws_region	AWS region. Default: us-east-1.
aws_profile	Optional. AWS profile to load credentials.
aws_access_key_id	Optional. AWS access key ID for authentication. If not provided, credentials will be loaded from environment variables or IAM roles
aws_secret_access_key	Optional. AWS secret access key for authentication. If not provided, credentials will be loaded from environment variables or IAM roles
aws_session_token	Optional. AWS session token for authentication

AWS Titan Models

These parameters are used for Amazon Titan Text embedding model

Parameter	Description
normalize	Whether or not to normalize the output embedding. Defaults to true.
dimensions	The number of dimensions the output embedding should have. The following values are accepted: 1024 (default), 512, 256.

Cohere Models

Parameter	Description
truncate	Specifies how the API handles inputs longer than the maximum token length. One of: START, END or NONE (default).
input_type	Use the Cohere embeddings model optimized for different types of inputs. One of: search_document (default), search_query, classification or clustering.

Example spicepod.yaml configuration, Cohere model

embeddings:
  - from: bedrock:cohere.embed-english-v3
    name: cohere-embeddings
    params:
      aws_region: us-east-1
      input_type: classification
      truncate: END
      aws_access_key_id: ${ secrets:AWS_ACCESS_KEY_ID }
      aws_secret_access_key: ${ secrets:AWS_SECRET_ACCESS_KEY }

Example spicepod.yaml configuration, Titan model

  - from: bedrock:amazon.titan-embed-text-v2:0
    name: titan-embeddings
    params:
      dimensions: "256"

Additional Information

Refer to the Amazon Bedrock documentation for more details on available models and configurations.